|
|
Absolute deviation, 绝对离差
. |+ ^% O, Y+ zAbsolute number, 绝对数
; M5 D2 D: p1 }; UAbsolute residuals, 绝对残差" m5 D2 f( Z+ w$ f0 V$ m) f; m
Acceleration array, 加速度立体阵
8 Q9 @& s% c& DAcceleration in an arbitrary direction, 任意方向上的加速度8 d! P: w7 S) X
Acceleration normal, 法向加速度0 k4 R( \( n+ k$ ]. ?
Acceleration space dimension, 加速度空间的维数- {( Y% d( j. \6 I0 o) X% a
Acceleration tangential, 切向加速度
8 N! w: q f* ]Acceleration vector, 加速度向量/ }) i1 v5 _( ^( n1 [* m4 s' ~ f
Acceptable hypothesis, 可接受假设
x: \5 l: o. g! p0 h( Y, qAccumulation, 累积5 T1 T) }5 [+ W* T1 j, H
Accuracy, 准确度# ]5 O3 T, }7 p. e
Actual frequency, 实际频数
$ j4 C1 J; P9 @* n6 b0 p+ P9 o6 HAdaptive estimator, 自适应估计量# P! m" t0 t: t0 Z# F- K7 z" J
Addition, 相加
8 A2 w0 F: l- Y/ g/ p% G" i- Z" R" BAddition theorem, 加法定理
: Q( ~5 g+ Q; x) pAdditivity, 可加性1 O& }6 x( I% W! {
Adjusted rate, 调整率
: n4 {- T5 w& M( rAdjusted value, 校正值
8 K2 y& E M( RAdmissible error, 容许误差: C e1 b6 @1 K3 M E+ o
Aggregation, 聚集性
6 ^8 D/ B' d- U8 FAlternative hypothesis, 备择假设+ o6 z$ l, @3 z5 {
Among groups, 组间+ l9 z/ t$ R K% g- m h
Amounts, 总量# N) x/ i! z7 h4 C* R8 [
Analysis of correlation, 相关分析
* Q3 E# b/ Z! }/ D: NAnalysis of covariance, 协方差分析
: N2 h& d" u+ U% c) m KAnalysis of regression, 回归分析5 y: {) y7 {( M* c6 X5 r0 T
Analysis of time series, 时间序列分析! L# T% U5 x9 H7 M1 c
Analysis of variance, 方差分析
# f, v8 Y# \# ]. A6 m$ GAngular transformation, 角转换
1 P& H5 I U U5 EANOVA （analysis of variance）, 方差分析" l& Q t% b5 ~
ANOVA Models, 方差分析模型9 f; Q2 |# l3 d$ g, U
Arcing, 弧/弧旋0 p2 K" s0 Y4 e: [1 @& T
Arcsine transformation, 反正弦变换8 H, N! K3 G) p5 G& `
Area under the curve, 曲线面积
$ n: g: B5 S5 f" VAREG , 评估从一个时间点到下一个时间点回归相关时的误差
3 J4 E# K' @5 u& N* V QARIMA, 季节和非季节性单变量模型的极大似然估计
`' U: I4 a2 h5 dArithmetic grid paper, 算术格纸
$ v) `8 u: _, r, {Arithmetic mean, 算术平均数" a! }1 k. [7 e& P. w
Arrhenius relation, 艾恩尼斯关系
$ u( `" f: {. CAssessing fit, 拟合的评估
$ A" o: R6 X. d: p/ S' c7 l% N. iAssociative laws, 结合律
8 R( ^( ]1 P) c( G) f2 s) zAsymmetric distribution, 非对称分布
- e4 j$ C: h6 {5 dAsymptotic bias, 渐近偏倚( B2 ^- R9 V! Q+ }7 L- A
Asymptotic efficiency, 渐近效率
6 {: b A9 H5 r) U1 K* T) U9 VAsymptotic variance, 渐近方差' `% _) r! }+ E O2 q! l& q, e
Attributable risk, 归因危险度
, I+ e6 y7 Z9 M( J+ H5 V. }& NAttribute data, 属性资料$ U, b2 ?* y& T! z- J0 e# f Z
Attribution, 属性
: M5 x& k; a& x" e; M; s- O# xAutocorrelation, 自相关 C! K. |$ [) Y4 D" s9 Q
Autocorrelation of residuals, 残差的自相关, d+ D7 L, `+ }( `! u1 d, K
Average, 平均数
% [7 I" T0 o1 yAverage confidence interval length, 平均置信区间长度9 I* e# j3 s+ ~ b8 c1 _
Average growth rate, 平均增长率
' f: w! V+ T7 W+ Y6 _' b3 HBar chart, 条形图
" c) |0 k. s% J( g) PBar graph, 条形图: q+ G# O9 q% j$ ?9 k( B
Base period, 基期+ ?# J4 e$ b* Y8 d1 b. N
Bayes' theorem , Bayes定理
* E* y! M/ {0 l6 J) ^7 `Bell-shaped curve, 钟形曲线
* O6 B# w: N2 @$ p ~- K$ |' fBernoulli distribution, 伯努力分布
5 P# S' V/ M& w1 z3 i/ Q% @/ F/ WBest-trim estimator, 最好切尾估计量
1 @3 K3 H/ s9 h2 y5 @- f# eBias, 偏性. T( `3 _+ D8 T8 N8 @& G
Binary logistic regression, 二元逻辑斯蒂回归9 T; ^6 Y" H: G) p# f2 A
Binomial distribution, 二项分布
5 j; P8 L# e5 [7 x& k& Q- }: Q9 pBisquare, 双平方4 Q" ^: p) n' ^$ h/ r1 M& t
Bivariate Correlate, 二变量相关6 w2 j4 n7 L; T4 U! q, [9 i' D
Bivariate normal distribution, 双变量正态分布- L: Y/ I, W2 K( Z# E9 d K5 x
Bivariate normal population, 双变量正态总体
; r2 `5 _: Q4 r$ cBiweight interval, 双权区间
3 ]# C' U( X" P* o" MBiweight M-estimator, 双权M估计量! x% z4 W. t: o; w
Block, 区组/配伍组: E5 G# r5 z6 S4 g6 Y$ G0 T2 w+ T
BMDP(Biomedical computer programs), BMDP统计软件包
5 f7 x$ R" p, ~7 z2 Y/ [Boxplots, 箱线图/箱尾图
7 {% D2 J2 E5 e7 O5 n) u) zBreakdown bound, 崩溃界/崩溃点2 X M" ]; y. `, h
Canonical correlation, 典型相关$ F% j: v% ]; {% r
Caption, 纵标目
3 A0 r, s3 _! O1 X$ p( _Case-control study, 病例对照研究
4 G7 n8 | Q, G; j( Q# WCategorical variable, 分类变量. ^: N9 z. f2 @0 i4 r
Catenary, 悬链线( |! q1 ~- D+ E0 n
Cauchy distribution, 柯西分布
: e9 m% R# v0 oCause-and-effect relationship, 因果关系
p0 {' j2 g, HCell, 单元- t+ I6 y' d0 f$ V, G% ~5 S: s
Censoring, 终检/ }) \* m, _2 p0 b
Center of symmetry, 对称中心0 H9 o, a- V# {
Centering and scaling, 中心化和定标# L3 {/ w2 t+ E7 o
Central tendency, 集中趋势, `# E; N7 r# ?$ A
Central value, 中心值: g& I) J: w0 y5 L, d1 }9 R3 \2 H
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
) P# l0 v4 y0 u/ tChance, 机遇
: n0 g% F: z, d {* O* N2 LChance error, 随机误差
: ^1 Y- \& d% _0 r3 M: i. v% w: lChance variable, 随机变量6 P* P/ v2 T$ J; M0 f
Characteristic equation, 特征方程( L8 f [/ X) X1 W# y
Characteristic root, 特征根
/ b- V# e+ K" a& s9 N* H0 ^Characteristic vector, 特征向量
+ I% b& e. C3 O1 ^3 A; L( RChebshev criterion of fit, 拟合的切比雪夫准则
; C( P8 b" p6 |- cChernoff faces, 切尔诺夫脸谱图! m1 j9 g3 f6 H0 e1 [, {! B
Chi-square test, 卡方检验/χ2检验/ W( r) C/ {& {8 U
Choleskey decomposition, 乔洛斯基分解, @" o" H- k0 \" J1 m8 Z: P
Circle chart, 圆图 ( w; a# P2 {+ L& z9 e* ]4 p
Class interval, 组距" {- N/ J% |+ H$ p7 M
Class mid-value, 组中值
1 f, i) y7 A( y/ N6 WClass upper limit, 组上限
8 l$ e* Y, `: f# t2 m' R/ f4 ?Classified variable, 分类变量7 x4 [ ~& t& X# j5 {
Cluster analysis, 聚类分析
) ]- p4 s& z# |4 Y+ {+ @Cluster sampling, 整群抽样" ~$ r. g0 w0 @3 N4 @/ P
Code, 代码
' f/ @" h& l- L2 TCoded data, 编码数据: v0 D, Q3 \, Y- T+ ~3 Z
Coding, 编码
4 [1 k$ O( k1 e, {" b8 XCoefficient of contingency, 列联系数8 O- R3 d7 ]: f" _
Coefficient of determination, 决定系数
! z6 P) i' A7 ]Coefficient of multiple correlation, 多重相关系数8 r3 ~3 Z4 r3 e' H3 N9 E) s( h: T
Coefficient of partial correlation, 偏相关系数4 b& Q6 K; H9 U4 [% Z' |
Coefficient of production-moment correlation, 积差相关系数* k1 ]3 {7 |8 N5 o( F% s
Coefficient of rank correlation, 等级相关系数. k5 V4 i* l+ P6 X" a1 C
Coefficient of regression, 回归系数
7 b% {! e- ~9 U1 m( \; o1 SCoefficient of skewness, 偏度系数% q) k% `/ Y) G4 t
Coefficient of variation, 变异系数
# W" H6 F" ]0 m5 S1 _0 JCohort study, 队列研究 F: w* M, g+ U1 D. ?7 M" D
Column, 列
. X3 B( X* Q* a( T- FColumn effect, 列效应+ m+ L, ?: b0 W7 D
Column factor, 列因素# w# T3 X6 H5 K) K0 m) A# c R
Combination pool, 合并- h2 S8 v1 |+ [& m4 S9 P
Combinative table, 组合表
( T7 s" E, }4 G( G5 [5 dCommon factor, 共性因子' S/ g# z( h7 i& v
Common regression coefficient, 公共回归系数" i1 L/ ~6 A! X: f7 V
Common value, 共同值$ a' G4 r3 s# q6 E( |8 g" |
Common variance, 公共方差8 w- t3 Y+ d, S
Common variation, 公共变异7 \+ |2 e6 I, f- v) \0 C* ?: O& [+ T
Communality variance, 共性方差
8 V+ {/ J& u5 Z# d4 Y: G1 rComparability, 可比性7 n# Z5 C. E, d3 f" m3 l& s8 ^
Comparison of bathes, 批比较
" ^0 [* L. A, Y# ^% W% r, fComparison value, 比较值2 d6 t# h! q4 {& T
Compartment model, 分部模型( u4 @9 K* j2 ~* K, [8 Y8 I
Compassion, 伸缩
7 U6 d) {9 l8 Z; T! u; V. C5 pComplement of an event, 补事件
9 S' u; }0 a5 ]* A) J: E* jComplete association, 完全正相关* G/ e" Q% r7 R, P9 b
Complete dissociation, 完全不相关
6 t1 {$ X7 X9 l) k J9 T8 o1 G/ vComplete statistics, 完备统计量
1 W# X9 O1 l' w; n) r# `Completely randomized design, 完全随机化设计, S, l5 n* V7 R" E
Composite event, 联合事件' }& r- Z$ Q" Q) c$ s8 G9 }2 }
Composite events, 复合事件! s1 P- H0 E" w! k m, f: ~" _
Concavity, 凹性
; O: E" s2 T) D, Z' A+ i* fConditional expectation, 条件期望
M. y+ t' l9 n5 |7 fConditional likelihood, 条件似然
- P7 \/ N9 l3 N* o* F' Z- OConditional probability, 条件概率
9 Y# I. R \$ V3 q* iConditionally linear, 依条件线性3 T1 c. z7 S& o
Confidence interval, 置信区间
f1 C% O( J: \- }8 XConfidence limit, 置信限$ ~- B( F: ^$ [' ]4 j K
Confidence lower limit, 置信下限: M3 g0 v' }0 W8 I2 w6 r
Confidence upper limit, 置信上限
; ]. f: f1 c8 I) a# }) ]; ZConfirmatory Factor Analysis , 验证性因子分析
7 }* S5 g3 S2 N% ]7 \$ ]: r% Z. OConfirmatory research, 证实性实验研究, \, N1 C8 c! s# T2 I
Confounding factor, 混杂因素
# X. d! S9 o7 A: J. EConjoint, 联合分析% u( h, n# T& a. ~
Consistency, 相合性
3 c5 L6 C& S6 Y4 i8 B9 g9 HConsistency check, 一致性检验
8 q4 | E. p$ o) wConsistent asymptotically normal estimate, 相合渐近正态估计
7 _& ] H1 a, U0 t8 JConsistent estimate, 相合估计
: U# ]1 g6 R7 V3 FConstrained nonlinear regression, 受约束非线性回归8 U4 K1 n8 Q+ I0 i0 ^4 W; v
Constraint, 约束
% R+ N, s u% iContaminated distribution, 污染分布+ N% V( [6 _5 |+ E
Contaminated Gausssian, 污染高斯分布 m. j0 P ? e) h, {) e, `
Contaminated normal distribution, 污染正态分布+ G j) A: [. a: @; ?) i
Contamination, 污染) t' }$ }) U9 {
Contamination model, 污染模型
; y g7 ~; M* y8 Q6 jContingency table, 列联表
; c8 m) {" j9 H( |Contour, 边界线, `8 F3 k1 ?& T3 Y/ a. C
Contribution rate, 贡献率$ U5 t- y3 X0 X$ q6 I
Control, 对照
+ k4 g$ i& c/ |/ SControlled experiments, 对照实验1 i+ r4 M1 }2 F* g0 R4 d
Conventional depth, 常规深度( ]- V m- j c9 R
Convolution, 卷积" t4 j5 Q% @$ j: ]
Corrected factor, 校正因子1 q; H6 w$ [5 D) O8 `4 @! I- e
Corrected mean, 校正均值
/ j6 \7 u% o8 }8 [2 D+ w- CCorrection coefficient, 校正系数
. e2 f4 u& ?- \. d( i" jCorrectness, 正确性5 Q( I) x6 `( S$ ^& v8 P3 m
Correlation coefficient, 相关系数
& h/ H1 J7 u; i* |. J: r; BCorrelation index, 相关指数% e. O0 m( _3 N! o- ?" w- d
Correspondence, 对应9 t' F; y8 {) H
Counting, 计数* ^( }0 ~1 u% Q- n9 ~
Counts, 计数/频数
! O: @3 b+ b) yCovariance, 协方差& F8 E; g& f5 e$ S
Covariant, 共变
C( D8 W2 N: ]Cox Regression, Cox回归6 N3 D! V$ i/ n, y6 S0 ^) G: m
Criteria for fitting, 拟合准则6 v8 z2 q4 H3 N% O8 m
Criteria of least squares, 最小二乘准则* P( T; \+ X2 ?5 x* V
Critical ratio, 临界比. O: b, V* e6 E3 W
Critical region, 拒绝域- G8 T; v3 i6 K+ A+ P4 i0 u
Critical value, 临界值
+ B _6 f# e0 K, l% jCross-over design, 交叉设计/ V+ L) n* Y9 ^/ f, v( U
Cross-section analysis, 横断面分析
7 ?% |( D" N! _- m9 L0 E' _# E8 }& oCross-section survey, 横断面调查1 p/ x( A4 F4 ~6 y
Crosstabs , 交叉表
0 ]9 y3 G" z. R' G/ o" `( ICross-tabulation table, 复合表
- d) A6 m0 I% F2 bCube root, 立方根
0 w5 F5 i2 t+ a. ?5 v+ |Cumulative distribution function, 分布函数
) g) D9 N, o3 ^Cumulative probability, 累计概率9 G5 }/ i3 ~2 s6 x, X% v5 b
Curvature, 曲率/弯曲* M) b# c. q6 |. u" |/ U6 v
Curvature, 曲率8 y' Q! h! k4 Z) H; E& u% x
Curve fit , 曲线拟和 0 G \4 |$ [7 f* [: j4 F
Curve fitting, 曲线拟合
p0 @( c7 t' @0 {5 l0 T3 n: K- k0 bCurvilinear regression, 曲线回归
$ p1 p/ g$ @$ p. oCurvilinear relation, 曲线关系
4 x+ I; Y4 l( FCut-and-try method, 尝试法
: n; z7 Q' m: {! {& b$ RCycle, 周期
) {- n/ D2 Y7 _Cyclist, 周期性
: U- M* w( D, OD test, D检验
1 f# j8 l# v( K2 K# g3 c1 y5 c+ ^Data acquisition, 资料收集* v, f" F4 u" O7 O. Q. X3 N. T( F
Data bank, 数据库
& l4 M6 g" D) u, z& d1 yData capacity, 数据容量2 w2 r+ f3 i# F+ B# u( [( q3 f
Data deficiencies, 数据缺乏
( x" a9 k3 k: D. ?" |3 I, eData handling, 数据处理
5 q- z& v, Z* @% x+ SData manipulation, 数据处理& A* G; H* f4 g# Y
Data processing, 数据处理$ M4 a7 @- i& B, W, ?& g
Data reduction, 数据缩减
6 H) D# R c! e* oData set, 数据集& B5 j$ g a+ M2 _3 @9 l: B# C
Data sources, 数据来源
* z9 a, @! x) D9 r) tData transformation, 数据变换% ?" W, T0 y& P H# |
Data validity, 数据有效性. m* [# K0 r$ O/ L; L' F; i$ V
Data-in, 数据输入
4 l- M+ C- q+ c- e5 M- aData-out, 数据输出6 f) c9 D( Q6 X" l9 M% Q# `) h- `- g
Dead time, 停滞期
' B& \7 q) i$ u$ u( B: aDegree of freedom, 自由度
5 Q) f# W& j4 iDegree of precision, 精密度, ]& |0 E, n. S8 F
Degree of reliability, 可靠性程度( e6 @/ Y$ X1 L
Degression, 递减/ ]0 d( E7 u& v8 L$ K. Z
Density function, 密度函数
0 B, S6 X5 L- f" M! B5 uDensity of data points, 数据点的密度& R8 ?# l+ `4 ^% Q S
Dependent variable, 应变量/依变量/因变量3 _1 L) B* J1 f! ^
Dependent variable, 因变量
& }8 }3 p! F2 W! e) A8 W* VDepth, 深度
0 `6 T! [ L+ r, q9 {, Q eDerivative matrix, 导数矩阵
- o9 m5 G7 O: J- a: k2 DDerivative-free methods, 无导数方法
( E! `; `. u4 x5 Y/ B4 QDesign, 设计
4 I; d' y3 A; \! I$ M3 [6 f$ @0 EDeterminacy, 确定性4 o* P/ |: R# f$ \5 D- t: Y2 G
Determinant, 行列式- p$ v' V P4 y. }. J
Determinant, 决定因素
9 r' H2 E9 t9 W9 e' O, sDeviation, 离差
1 {2 L- P$ r' z( Y( SDeviation from average, 离均差/ Z% U# _2 s) c! ?' f
Diagnostic plot, 诊断图1 Y3 s5 m1 K& s# d" Q, p
Dichotomous variable, 二分变量
& k% k- m9 ^# f1 H0 ]$ mDifferential equation, 微分方程4 V/ b" R0 H5 {8 x* a
Direct standardization, 直接标准化法
0 [) [5 T% k& J" iDiscrete variable, 离散型变量
4 B; m% [. ~( M$ g7 L' B+ ]9 CDISCRIMINANT, 判断
. l# ^' d+ ^4 W# Q$ ^9 o }Discriminant analysis, 判别分析
- d- n5 e9 v; S" h/ P5 K4 @Discriminant coefficient, 判别系数# J, i* x5 T& j; C5 S/ t% X3 S' ]
Discriminant function, 判别值: t" h& o* ~4 \
Dispersion, 散布/分散度
2 p3 E/ _ u( J/ t E# O- SDisproportional, 不成比例的
, H) D, S, r2 `8 l3 l" hDisproportionate sub-class numbers, 不成比例次级组含量5 d- G, x5 b: ^" a9 R1 M. J$ w
Distribution free, 分布无关性/免分布
- @! o5 L3 R( ~' s: Z3 W1 lDistribution shape, 分布形状, x+ ^7 T8 `3 y& g: t$ D
Distribution-free method, 任意分布法
! {6 Q* p5 V: y! tDistributive laws, 分配律
. |- \3 x3 D7 q# S* w) M* _Disturbance, 随机扰动项9 F- @" o9 r& O3 w8 c8 W
Dose response curve, 剂量反应曲线
5 `5 s+ t9 F' r7 |2 j0 A' X+ O/ rDouble blind method, 双盲法4 Z& j" l2 I, S; y. x+ L
Double blind trial, 双盲试验
/ i7 S) k; h, M, R2 S" LDouble exponential distribution, 双指数分布
1 Q7 K- r, z$ m% O4 p* MDouble logarithmic, 双对数3 m& d6 d' F' P& ^2 z
Downward rank, 降秩
' {+ M2 x/ \* ?5 v5 v- }Dual-space plot, 对偶空间图1 w# J2 G6 {( m' X
DUD, 无导数方法
* |6 B% H, }, Q; I! }, u# F A1 L: _9 vDuncan's new multiple range method, 新复极差法/Duncan新法
6 z: A5 a7 [0 `( {Effect, 实验效应
p/ k; V& p3 P) Q: zEigenvalue, 特征值6 f0 `* Y5 y9 N5 y! Q
Eigenvector, 特征向量
( t0 x' A2 w7 @( wEllipse, 椭圆/ F, ~; R* u4 Z
Empirical distribution, 经验分布
! p8 N0 s) V0 b9 F- u8 L7 GEmpirical probability, 经验概率单位& W9 V. v+ {# O: C2 c- x& v
Enumeration data, 计数资料8 R! N. E8 s4 Q
Equal sun-class number, 相等次级组含量
8 C& d" x/ S# F4 I- ]Equally likely, 等可能
+ {/ z0 G6 u5 b& i0 U" iEquivariance, 同变性
" f* @# L1 \$ X( D7 ]$ UError, 误差/错误! z" V% r6 N! x/ @% j3 }5 |
Error of estimate, 估计误差
% J- V1 T1 L. ]9 R* A' ]0 ZError type I, 第一类错误
: C1 \* \/ o, sError type II, 第二类错误
0 P; F C+ A- {2 yEstimand, 被估量/ _, V* q7 |4 q g, I- f" [* k C' n
Estimated error mean squares, 估计误差均方 p" s; g) m2 ^+ u& ^% L
Estimated error sum of squares, 估计误差平方和0 Q" u; G5 ]+ H; X2 y9 |
Euclidean distance, 欧式距离
9 G* a; }+ L# c2 ^% J8 N( k% J4 gEvent, 事件
1 Y: M3 h7 T* l6 I4 ?7 xEvent, 事件5 A2 ]; f4 l: {
Exceptional data point, 异常数据点
, ?5 S( r- |& j: N( cExpectation plane, 期望平面' v; g) u2 S2 l
Expectation surface, 期望曲面
. V9 \ y4 P/ e1 z5 J+ nExpected values, 期望值
' h' V( u$ v' w; [Experiment, 实验
" t# n" B1 L9 i: k5 S9 u0 BExperimental sampling, 试验抽样
' [8 W o' a2 y* X7 ?Experimental unit, 试验单位7 Y$ j) e1 @! [; U0 Y5 s
Explanatory variable, 说明变量
& j: r" |1 S: z+ ~. v4 @1 v. v2 m. KExploratory data analysis, 探索性数据分析
f: D4 e2 b# n) M U# }, l! \Explore Summarize, 探索-摘要; S( ?1 V/ i$ y9 _
Exponential curve, 指数曲线1 x I+ a, h! P6 f3 V# N/ Z. G
Exponential growth, 指数式增长
0 W# H* I4 U: e% e+ UEXSMOOTH, 指数平滑方法 7 v0 v- g1 v& U' J# C _5 ^
Extended fit, 扩充拟合* w5 k) g, W8 s% C0 E/ f
Extra parameter, 附加参数
) s6 M) w& \' i" t: I4 GExtrapolation, 外推法& x$ c5 \6 W( y u/ i" v) d$ x
Extreme observation, 末端观测值
+ v- T5 n5 K$ ~% b$ i% q& k4 v7 JExtremes, 极端值/极值. B( ~% m0 U1 D% h: a8 j9 e A
F distribution, F分布
: h/ I0 T3 w9 E' Q. N" F# \( R& n% [- OF test, F检验/ L9 [ e7 L N
Factor, 因素/因子
x# e$ }& L# E0 b4 E2 h' ^Factor analysis, 因子分析
, b) V1 N/ E g" n2 ]8 l U7 [Factor Analysis, 因子分析! P* H4 Z1 G+ L% k6 S# ]
Factor score, 因子得分
' _! d& q' Q8 O, I0 sFactorial, 阶乘- U% a; t; w Y( N W
Factorial design, 析因试验设计* D x! Q; _( S* k3 v
False negative, 假阴性
0 j: T" v, X3 U3 n0 pFalse negative error, 假阴性错误
1 c! c( `0 D& cFamily of distributions, 分布族$ V- e! z: H: Y; \/ q9 B4 Y
Family of estimators, 估计量族
9 G5 M. b/ f: z2 ~Fanning, 扇面 p3 z0 _( H8 l6 u% z7 n7 D" p
Fatality rate, 病死率
8 Q9 i# ~2 l1 e7 ?# F4 zField investigation, 现场调查- G& e+ Y# V, T
Field survey, 现场调查. |& v! V. ]3 O0 r" ^) Z" P
Finite population, 有限总体2 q1 U! ~2 r2 n! U2 s
Finite-sample, 有限样本' Q$ {* T9 m9 P2 C
First derivative, 一阶导数2 L6 P0 |& U5 O E4 ^
First principal component, 第一主成分7 E, L% E- F: W
First quartile, 第一四分位数
3 D* x" K. h& U5 w- r r9 [; ^0 |Fisher information, 费雪信息量
2 R z5 w" O& hFitted value, 拟合值! b! {- r! U9 O( P$ [6 K; I w
Fitting a curve, 曲线拟合& O1 x9 E6 H/ C- _
Fixed base, 定基! j- K* Z8 r. H; y1 m1 h9 f
Fluctuation, 随机起伏
( U5 e1 N2 L8 @3 x. h0 sForecast, 预测
4 S5 e* O+ a6 qFour fold table, 四格表
$ X0 H$ j- b9 n& z) S* uFourth, 四分点4 S% b9 e7 G1 D+ u
Fraction blow, 左侧比率, n0 U$ P) J3 f; l) g
Fractional error, 相对误差
& p" x; f# _1 f0 i1 E4 jFrequency, 频率
" p9 C1 I7 G8 j+ DFrequency polygon, 频数多边图- p. ~5 u; h8 {2 |
Frontier point, 界限点' {* T8 H* n0 h+ A. V S
Function relationship, 泛函关系$ x6 `" I3 b8 ]9 x9 _; r" `
Gamma distribution, 伽玛分布
8 `1 ~. e3 j. u& n2 yGauss increment, 高斯增量/ z& ^$ `5 f4 a& Y) v- X5 {
Gaussian distribution, 高斯分布/正态分布
# ]; u( A8 n" vGauss-Newton increment, 高斯-牛顿增量
- w' Y1 o; r+ F5 R6 r% t( E8 iGeneral census, 全面普查" e$ A" m: |$ h& T
GENLOG (Generalized liner models), 广义线性模型
8 f0 n$ d* u9 d2 @6 f+ DGeometric mean, 几何平均数+ j0 N' F7 j: }- T, X2 q: W
Gini's mean difference, 基尼均差' s9 I; D; p$ d. A% c
GLM (General liner models), 一般线性模型
: u3 m( ?$ ^; G+ ~; [Goodness of fit, 拟和优度/配合度9 i8 l- j5 l5 V) Q& E
Gradient of determinant, 行列式的梯度
" x3 u! E: y# _2 G j: w/ ? ?Graeco-Latin square, 希腊拉丁方
# i8 Q$ M# k& M. `3 F, x$ z: KGrand mean, 总均值
' R. N% q( P6 c% LGross errors, 重大错误
7 v' G2 k! X) h( |, |! [$ vGross-error sensitivity, 大错敏感度3 d* @' z4 d( B: ]( |
Group averages, 分组平均
7 A; f0 r- U* e' W2 D% R- g/ bGrouped data, 分组资料
; m6 Y/ w1 L% H9 NGuessed mean, 假定平均数0 h6 V4 ?3 k/ x# w* i1 L
Half-life, 半衰期* j4 ~+ w, O# z7 s( ]6 V: ?% v; J
Hampel M-estimators, 汉佩尔M估计量
/ N$ y3 `* U2 X. W- m) DHappenstance, 偶然事件, q7 {+ B8 Y" ?8 K' V" H
Harmonic mean, 调和均数
" `' j: V$ \" K. `5 PHazard function, 风险均数
1 V- H& i4 h3 C8 j2 wHazard rate, 风险率& j( T5 v7 w7 c/ K
Heading, 标目 , e7 \ C# N0 O' ?) v/ t6 {) C
Heavy-tailed distribution, 重尾分布& T# B( G) o0 U5 o+ j, b! d
Hessian array, 海森立体阵" T3 j3 w' J4 t( h$ W: e
Heterogeneity, 不同质
4 \! {6 b! c6 k% @' [- a& {( |Heterogeneity of variance, 方差不齐 ; ?$ H3 Q8 d3 E6 m& |( v' Y
Hierarchical classification, 组内分组
6 h& A$ [3 c" Q+ N- N8 i5 vHierarchical clustering method, 系统聚类法" S; }) d( v% g6 F3 D) D
High-leverage point, 高杠杆率点, ?+ m* x+ J, b! z) A, k0 u8 x
HILOGLINEAR, 多维列联表的层次对数线性模型
9 ~1 @% u' `2 T1 YHinge, 折叶点
6 d' N3 i! x1 g+ G& [8 FHistogram, 直方图6 a+ d w8 N B
Historical cohort study, 历史性队列研究 ( f/ K$ k( m6 \" D0 i* D. t
Holes, 空洞
" X$ \+ {0 V# g$ AHOMALS, 多重响应分析- S8 T* e- @+ b8 G# f, z U4 w
Homogeneity of variance, 方差齐性& f- V7 j1 T8 t, n8 O" T
Homogeneity test, 齐性检验
6 Y3 [7 \' B" V0 x( MHuber M-estimators, 休伯M估计量. `5 O4 K# }; ^1 Q( |
Hyperbola, 双曲线9 T8 h, }. P- h/ v5 i
Hypothesis testing, 假设检验0 S# P9 G% ~8 c& E
Hypothetical universe, 假设总体2 @0 F& B/ ] P; {% K; |
Impossible event, 不可能事件
# m; p: |( x% M U1 @Independence, 独立性
0 p( c. X& ~2 b* r$ J3 s# sIndependent variable, 自变量
& X9 o# G8 L$ `# E& ^& cIndex, 指标/指数
1 e- _ y' }) E. M9 w& ]( D1 KIndirect standardization, 间接标准化法
; X& e- I3 T9 p% U' a, p8 [. oIndividual, 个体
9 m3 q" G b q/ H% W( yInference band, 推断带
- O! U. p* X2 e9 p& C- GInfinite population, 无限总体! I% ^4 t9 F4 n. J2 Z$ p% ]
Infinitely great, 无穷大; I" q' Q* _' D
Infinitely small, 无穷小
. ?1 N* j, \0 }Influence curve, 影响曲线
% r6 g3 h. Z' `- l, P/ v& c1 m; UInformation capacity, 信息容量* y8 Z& p& ^$ ]6 [/ _ |' Y+ \6 a
Initial condition, 初始条件
* w- ~8 L- m, p: Q0 C2 h0 qInitial estimate, 初始估计值
/ Y G: k. u2 K4 ~2 D/ C1 [& EInitial level, 最初水平5 B4 p+ p v1 y D
Interaction, 交互作用% S: o% c+ \8 U; I Y
Interaction terms, 交互作用项6 p) ^, ?' J1 o, T2 e: @' e5 I" k
Intercept, 截距. T$ g( e/ \3 n7 y$ ]6 R8 ?
Interpolation, 内插法
' u! K% [# s% n, rInterquartile range, 四分位距/ M/ k4 H! |% G: E) q% h2 X8 ~
Interval estimation, 区间估计
7 X' D% e% q. t; lIntervals of equal probability, 等概率区间6 s9 {3 O3 J% A! U0 p3 n
Intrinsic curvature, 固有曲率) _6 ~, R' ~- y7 z6 C T) ]
Invariance, 不变性
. f0 K( z c% r& H+ e4 GInverse matrix, 逆矩阵
. M |. C/ D9 E9 C. i5 U1 }Inverse probability, 逆概率
6 p3 z% Q' D4 g4 WInverse sine transformation, 反正弦变换. F# G1 c3 D1 S1 d6 a: S
Iteration, 迭代 * D) l4 B8 }' \1 H* p2 S# ~4 ~
Jacobian determinant, 雅可比行列式% s2 \0 D. V3 r9 Q
Joint distribution function, 分布函数( L; V# [; J( r9 l
Joint probability, 联合概率
: F& L: p* l5 q0 ]" RJoint probability distribution, 联合概率分布
! Y1 P/ E8 S: _% I5 ]* z( VK means method, 逐步聚类法
n8 {4 a) N+ v: P( X4 O7 Z6 jKaplan-Meier, 评估事件的时间长度
2 `# B7 L: V P3 Q! Y+ B7 fKaplan-Merier chart, Kaplan-Merier图3 g0 ?6 E& R& O4 y. u
Kendall's rank correlation, Kendall等级相关
* \* n% X4 J& n7 qKinetic, 动力学
- \4 }- F, r/ A I2 d5 OKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验4 o7 j J1 I/ Y9 F; g
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验7 _2 S- s9 P% H; ? r) z7 S6 v4 b7 e
Kurtosis, 峰度6 T& C, H( @8 K1 d. {6 ]4 L
Lack of fit, 失拟7 I0 a& a$ }( ~- D: ]+ L6 P4 W5 w& g
Ladder of powers, 幂阶梯
; [3 F7 h+ l: G( Q: `Lag, 滞后
4 C8 S$ G3 j; s- O- \" V4 m# NLarge sample, 大样本- j5 @3 T" |* w8 I$ K" A
Large sample test, 大样本检验7 j+ m X9 w, `, E, e4 f
Latin square, 拉丁方
- \/ U8 P: b0 O; J9 }- rLatin square design, 拉丁方设计
& `5 z4 \( E: F& m' [Leakage, 泄漏7 x$ U6 ]! T1 v; n2 w
Least favorable configuration, 最不利构形: f: a: Q+ r. [
Least favorable distribution, 最不利分布9 C3 J, r# X4 V5 ^
Least significant difference, 最小显著差法
8 {# c+ }2 @+ _. [2 b( e( z) DLeast square method, 最小二乘法1 p, A; W) S7 d# t! c3 L
Least-absolute-residuals estimates, 最小绝对残差估计6 _& [7 x9 b. T8 J
Least-absolute-residuals fit, 最小绝对残差拟合
$ e' _; T* V/ XLeast-absolute-residuals line, 最小绝对残差线
+ J: H4 M. L8 D- h' I) FLegend, 图例
5 E9 t7 e9 L- @4 m! a0 N5 uL-estimator, L估计量
2 D4 Q" o/ h3 j6 RL-estimator of location, 位置L估计量" h: B/ E, V, L) H
L-estimator of scale, 尺度L估计量# {( B/ _- A8 ^) T+ p6 t
Level, 水平
6 l4 Y7 |' I% a5 ]; O8 l1 i! }5 YLife expectance, 预期期望寿命- ~0 _1 s* {( K4 R! ]3 H% i1 `
Life table, 寿命表
; U" M( K3 p9 ^3 S# {# zLife table method, 生命表法5 u, C+ e- @) D
Light-tailed distribution, 轻尾分布
' {6 ?4 N& q5 F- h5 T! ULikelihood function, 似然函数% G7 t& F* ]* [' B( s
Likelihood ratio, 似然比
+ v1 Y6 Y j9 O% i0 s/ v8 }line graph, 线图; ]& b$ ]& Y7 S- B! l" T
Linear correlation, 直线相关$ _' |1 H4 b- [
Linear equation, 线性方程) n7 n2 D" d# ~1 Y) ]7 l9 ^; Q
Linear programming, 线性规划
& s2 E( \! v0 v( c) A3 y/ Z" |0 n/ {Linear regression, 直线回归
3 X, X$ [4 {$ }( e' G% E) y9 J& l, i8 G/ TLinear Regression, 线性回归
+ o% i9 _3 J/ a* |Linear trend, 线性趋势
0 Q7 |+ a; m+ D7 f7 Q R4 aLoading, 载荷
5 y# ^. ^" j6 A4 s: yLocation and scale equivariance, 位置尺度同变性. ]% U F, z" i& J3 Z
Location equivariance, 位置同变性
3 u' u% L% A+ a d* q0 B. yLocation invariance, 位置不变性! A/ ?6 H& f0 I. V4 O
Location scale family, 位置尺度族7 ~- K! H+ M' l2 r: M. p
Log rank test, 时序检验
7 |% e/ X' r, j3 O* K: _Logarithmic curve, 对数曲线9 @: U' }1 N! ~& g
Logarithmic normal distribution, 对数正态分布
& x6 S0 L; n* b+ J" @. {/ ]) ^5 SLogarithmic scale, 对数尺度
& K% x& Q9 O' ~! d+ x" [# ELogarithmic transformation, 对数变换
; a6 w' t J# O: F" P# {& b% rLogic check, 逻辑检查
" {( d- |0 p/ Q* B6 VLogistic distribution, 逻辑斯特分布
! r, Q- K" W$ F' |% O/ I/ wLogit transformation, Logit转换
4 B0 U* X6 Z* f! TLOGLINEAR, 多维列联表通用模型
! Z$ r% j& _$ s) [& R0 t/ |Lognormal distribution, 对数正态分布7 h9 G4 n, v' X
Lost function, 损失函数
S0 f$ W4 U Y5 w6 v3 mLow correlation, 低度相关
+ Y, P! b, }$ Z8 @- ~' y7 fLower limit, 下限8 [8 a0 T7 e, s' U8 m
Lowest-attained variance, 最小可达方差
* o6 b& Z# B/ S/ BLSD, 最小显著差法的简称
# d) k6 N. z$ B3 uLurking variable, 潜在变量
6 j4 w( G2 r4 A! x& IMain effect, 主效应* a: I# M5 E3 ^0 |9 M
Major heading, 主辞标目5 D: J! T3 v! [5 `& y* ~
Marginal density function, 边缘密度函数, y# ~6 g, R. ^. F7 L! v/ _
Marginal probability, 边缘概率1 k+ @. k+ g8 j
Marginal probability distribution, 边缘概率分布
K; Y: a) o( c0 o' h, z+ H) |" c' YMatched data, 配对资料1 D7 J i4 v2 K
Matched distribution, 匹配过分布/ }. D6 E' l0 ^* G: P4 x: F% W$ E
Matching of distribution, 分布的匹配
6 z7 u( b5 ?, ^7 ^, W" F& U4 H0 fMatching of transformation, 变换的匹配, c0 _2 E% \$ v$ w
Mathematical expectation, 数学期望
, A: T8 y8 x7 i0 V. p# R4 AMathematical model, 数学模型
; }+ }3 f( y& v4 ^' Y0 VMaximum L-estimator, 极大极小L 估计量) M6 H) _4 W8 Z; B2 S2 x3 O: m6 F
Maximum likelihood method, 最大似然法
) r9 I t! d. [2 H7 rMean, 均数$ o7 W5 f$ `: i; L' p% `
Mean squares between groups, 组间均方
8 O: Z7 `3 K7 x% H2 E8 g9 J2 p" cMean squares within group, 组内均方
/ V; D. N* W4 O f1 o- aMeans (Compare means), 均值-均值比较5 u& E6 q" d2 }1 B' c0 [! e+ e! x
Median, 中位数
& K5 t3 O# X0 }Median effective dose, 半数效量
$ s3 {/ n# \+ U. I5 c8 RMedian lethal dose, 半数致死量% W7 G, y* H5 P$ f# |, L
Median polish, 中位数平滑
/ _2 ]- {# h% C, p8 LMedian test, 中位数检验: D- F7 g. X0 t$ x- T
Minimal sufficient statistic, 最小充分统计量" a) A' O6 Z' M$ t2 V$ c
Minimum distance estimation, 最小距离估计. A% g" o% D) V' i
Minimum effective dose, 最小有效量3 d' n7 b$ _& m' ~# ~% R
Minimum lethal dose, 最小致死量
) ~ p" ~6 |0 s# Q2 c1 lMinimum variance estimator, 最小方差估计量
) w( i! w& b/ o4 g- H: r" ~MINITAB, 统计软件包
# P1 [- H( c1 K! _8 Y4 J0 dMinor heading, 宾词标目3 J, Y8 c6 K: ? E) l
Missing data, 缺失值
( f6 U0 E/ ?! WModel specification, 模型的确定& o/ @" k0 X- t! m" Y( y
Modeling Statistics , 模型统计5 C6 U8 ?1 x5 T q
Models for outliers, 离群值模型; h, m4 b4 S# N) M' l
Modifying the model, 模型的修正' p8 h0 e( w! `7 R2 n
Modulus of continuity, 连续性模
. M- E+ @8 n7 V i( J9 qMorbidity, 发病率 * m8 ?, o% b. F* ]5 z. _
Most favorable configuration, 最有利构形
1 _. m* ^, R& o5 iMultidimensional Scaling (ASCAL), 多维尺度/多维标度
* J* `& S7 p0 f: KMultinomial Logistic Regression , 多项逻辑斯蒂回归4 W# k0 P$ p6 N' i' }$ v' [
Multiple comparison, 多重比较# q0 a( s, b8 h. l( V
Multiple correlation , 复相关0 G: L. s. H8 h- M) x; U7 n
Multiple covariance, 多元协方差
; ~# N5 T8 [- R1 GMultiple linear regression, 多元线性回归+ u0 A+ } s" }: u3 P, ~
Multiple response , 多重选项 c; B6 M' y `
Multiple solutions, 多解, c5 K/ y' u$ g2 W# K3 c
Multiplication theorem, 乘法定理
. g; L" _: L" C3 PMultiresponse, 多元响应
6 @: N. g4 [6 ^0 j+ c& ~% [Multi-stage sampling, 多阶段抽样
, M0 h$ Z$ a' y! e) B9 ]. d# i9 Y2 PMultivariate T distribution, 多元T分布3 i3 |, Y8 a* H; J+ @& R. H, O: \
Mutual exclusive, 互不相容
+ W6 B+ z7 N. |) q' M+ e+ CMutual independence, 互相独立
+ Q8 c2 z `$ CNatural boundary, 自然边界/ Y4 l- H( e F' `5 ]
Natural dead, 自然死亡7 F3 g/ {2 n# D- X! V7 j
Natural zero, 自然零
8 P$ Y! F9 M2 y4 c. @6 u+ i1 S! sNegative correlation, 负相关* e- [, K) h* s1 |
Negative linear correlation, 负线性相关, [7 g" i9 _' o$ Y
Negatively skewed, 负偏
' N) u J# p* l' _- i7 H! C+ bNewman-Keuls method, q检验1 v4 C' x: _% u% b- I
NK method, q检验8 g5 R- N5 X' I) f* o
No statistical significance, 无统计意义
8 e {7 ?: o/ x1 N3 n; {Nominal variable, 名义变量
4 e" T( g7 `, [Nonconstancy of variability, 变异的非定常性
; U! }$ L6 `+ c9 S5 j# ANonlinear regression, 非线性相关
4 G. p4 y7 b0 u* [) C9 f3 M) WNonparametric statistics, 非参数统计; }3 ?4 M* b6 d: Z
Nonparametric test, 非参数检验' O2 z; L0 |+ N' G* ~
Nonparametric tests, 非参数检验
' B7 H9 y1 S9 [Normal deviate, 正态离差+ [8 d- }# I5 f6 Q; ?) ]
Normal distribution, 正态分布5 |, ]$ P! u, K' X+ e, q2 o
Normal equation, 正规方程组
2 ~1 a( \) Y% b+ kNormal ranges, 正常范围
( u: S+ J& K2 z' G W7 |5 c% eNormal value, 正常值6 N$ J! L# P3 W7 L' z9 ^
Nuisance parameter, 多余参数/讨厌参数! x$ w. }2 T4 W. p) z* J6 O# B
Null hypothesis, 无效假设 $ F# A$ m* A* Z) {8 J3 E9 T8 y" Y
Numerical variable, 数值变量
5 n$ t4 |- M* B* T/ yObjective function, 目标函数
2 b# v( |& w& _/ D0 dObservation unit, 观察单位) W# [$ K8 `- p3 k) [* Y2 V3 q
Observed value, 观察值4 v2 S) p+ B: C- U- e- Y
One sided test, 单侧检验/ V6 e: K' v0 N& S/ V
One-way analysis of variance, 单因素方差分析6 k: e% V5 _" N1 v% s
Oneway ANOVA , 单因素方差分析
+ F/ n8 b; N/ w: [$ [Open sequential trial, 开放型序贯设计
! v) _: ~* I. s0 g$ E2 KOptrim, 优切尾
; ?& X) h, k6 h' xOptrim efficiency, 优切尾效率: t9 E; h8 E3 _5 U' R
Order statistics, 顺序统计量6 n0 o0 l% w# Z& U6 D. H$ Y
Ordered categories, 有序分类
% C. }# c( m% TOrdinal logistic regression , 序数逻辑斯蒂回归, [2 j" }- U. |7 Q7 f M: C
Ordinal variable, 有序变量
) s' N" E) P/ \1 ~" }3 f1 a: o1 pOrthogonal basis, 正交基
& [8 r- S x2 r' h) E0 bOrthogonal design, 正交试验设计( i7 F9 ]7 y" a0 s
Orthogonality conditions, 正交条件
* R5 ~5 X+ k4 S9 } p( I# M, M9 a# aORTHOPLAN, 正交设计
7 O, ]/ l& L) Z! Y- kOutlier cutoffs, 离群值截断点! ^3 t7 r" s4 b) m1 S: q
Outliers, 极端值
0 D; T, H% V7 C7 `: c8 z3 kOVERALS , 多组变量的非线性正规相关 * H) q& b) r- k( b
Overshoot, 迭代过度/ U z. K7 n4 c3 u
Paired design, 配对设计, ~+ E* j& C0 `0 I8 _! C' n
Paired sample, 配对样本
2 ?; K! j6 c, Y+ H! W1 d2 ~/ OPairwise slopes, 成对斜率( a& d, i( ~8 [! ]
Parabola, 抛物线! \3 q( L6 p2 r4 B
Parallel tests, 平行试验
) h. s; F7 s8 L2 L6 q! lParameter, 参数/ `- S0 `$ U/ Z2 E
Parametric statistics, 参数统计
, ?6 a9 e O; [2 A- T: Y( h8 RParametric test, 参数检验5 `7 f- R# E* i# S. ?
Partial correlation, 偏相关) Y- ?7 }! m1 a$ i
Partial regression, 偏回归" U9 ?1 r) k$ B
Partial sorting, 偏排序9 r: |8 e4 N9 K( b/ L C. r
Partials residuals, 偏残差! C) e7 _) @7 o" _
Pattern, 模式, M* l5 K0 K0 p- ?
Pearson curves, 皮尔逊曲线# V+ B f8 y" ^9 l2 u0 z, A9 m
Peeling, 退层# X- e! ]) x+ p# x4 y$ e I
Percent bar graph, 百分条形图
; a4 L7 }4 y& ~- H! D, g3 PPercentage, 百分比
7 V* X1 O6 y. ~( ^1 dPercentile, 百分位数
3 O9 Q4 D! \7 t+ nPercentile curves, 百分位曲线
0 t2 E, W% s U- ?Periodicity, 周期性& S3 x( |9 w A) _6 {
Permutation, 排列
; W* h/ |- t s2 I- {5 J; ^P-estimator, P估计量
/ Q* a- C5 m( l, o3 v) W6 OPie graph, 饼图& b& H6 B7 T3 B" @/ O# t' U
Pitman estimator, 皮特曼估计量
0 P0 U8 D4 a& tPivot, 枢轴量
' x& ~$ W& n, SPlanar, 平坦
! u/ _2 I9 n& ]3 T6 O. g7 S7 c, UPlanar assumption, 平面的假设- s3 L! g+ B) x; @& |# S! x
PLANCARDS, 生成试验的计划卡
( _! S/ D+ x9 fPoint estimation, 点估计5 l+ v) x2 p0 \5 v' S
Poisson distribution, 泊松分布9 I" f/ b5 o+ i5 L- e- ~
Polishing, 平滑8 C1 D0 s- q+ E& l, C7 `2 s
Polled standard deviation, 合并标准差+ |/ B3 A! S* ^5 E3 o9 S1 q
Polled variance, 合并方差9 Y* x* C" U7 U! O9 r
Polygon, 多边图4 z _; x( D# u8 s1 G% g% m
Polynomial, 多项式
: L* f% x1 h' k" \Polynomial curve, 多项式曲线
7 J/ b( r4 Y- t+ H) I& ]' Y" Z* i$ IPopulation, 总体
# |& P. W% q% e& H( s8 \9 ?) NPopulation attributable risk, 人群归因危险度& o% U/ L/ ?9 _/ E7 _; p
Positive correlation, 正相关
9 d, h$ I/ T9 c! z. HPositively skewed, 正偏: O' ~( U/ L5 v. ~
Posterior distribution, 后验分布
5 v2 J ?( _% _" EPower of a test, 检验效能
: W2 P- u' U0 [5 l) j) P* IPrecision, 精密度8 N, B8 T' r3 }
Predicted value, 预测值 G* Q0 i* K$ A; m( p
Preliminary analysis, 预备性分析3 D. U) g% p8 k/ w; p( @
Principal component analysis, 主成分分析
8 k/ [ f6 n! o, E+ e9 L7 u/ `$ a$ PPrior distribution, 先验分布3 |; T! _9 K& q
Prior probability, 先验概率5 Q& f' I/ c. n4 q% `
Probabilistic model, 概率模型* R" O8 A* j; r' b0 a: M$ j. a' l
probability, 概率
$ r, h& l& e& I2 Z# c$ HProbability density, 概率密度
5 { S8 `4 e0 } W* |Product moment, 乘积矩/协方差
8 ?# F; c2 c; C$ j6 X$ f# D! y9 f6 k- VProfile trace, 截面迹图
- w9 O1 N8 L$ `9 n' j- t9 B% J' Y6 xProportion, 比/构成比
3 r m3 g* U1 UProportion allocation in stratified random sampling, 按比例分层随机抽样" c. L; j; k4 u6 a" U
Proportionate, 成比例
" g5 ]7 ^5 o) S* r& \: sProportionate sub-class numbers, 成比例次级组含量( I8 X' x5 V. O; ]
Prospective study, 前瞻性调查
+ U" T8 z. b. X3 O# J, E8 Y; nProximities, 亲近性 ( q& O% w7 [6 O5 H9 H; U
Pseudo F test, 近似F检验% \, P3 ?5 ?) X1 I8 p
Pseudo model, 近似模型9 l' K1 j$ {: F; l, w3 o- V
Pseudosigma, 伪标准差& t3 y8 F" V2 h# L% A; R
Purposive sampling, 有目的抽样
0 |+ ~0 ]+ t; B) {% P" SQR decomposition, QR分解
6 @$ o7 q; {( `; H+ X2 e; U' V% e tQuadratic approximation, 二次近似
# B6 R; a- k3 u; _9 X TQualitative classification, 属性分类
2 n$ l/ B( y3 P0 l5 f% L/ c; _Qualitative method, 定性方法
# \' U: V8 P/ m- X0 oQuantile-quantile plot, 分位数-分位数图/Q-Q图) A+ s2 W+ L& _. ~8 c7 S6 d- t3 `/ J
Quantitative analysis, 定量分析
\" h: J" e; J' r% b; uQuartile, 四分位数 F6 _2 x) D1 W m- L/ `. X
Quick Cluster, 快速聚类6 z7 Q: b# I5 B9 A
Radix sort, 基数排序
) _+ w8 u% h7 }0 \5 o2 XRandom allocation, 随机化分组9 p6 F3 d& l1 C
Random blocks design, 随机区组设计: H* ?' ?+ t, @! C- L0 P
Random event, 随机事件) C* l$ X& c/ [( m9 R
Randomization, 随机化6 A1 C' m1 l, B% e3 E) J+ ?
Range, 极差/全距4 I3 W! @' `6 {2 f' x5 R9 s" {
Rank correlation, 等级相关
3 M, g/ E" L9 d0 p6 I# f$ { @Rank sum test, 秩和检验5 S4 D" ]. x; [+ v7 j; Q
Rank test, 秩检验4 a/ z- }6 V. @9 M9 R
Ranked data, 等级资料
$ \' F R/ w) [% V3 r- D! _ sRate, 比率- X% n% |- Y( x0 U" a
Ratio, 比例 d0 R& z" y+ k5 `
Raw data, 原始资料0 b" v3 F* @" W- _+ U
Raw residual, 原始残差
1 S. F+ O* m( t) O* W8 v- G tRayleigh's test, 雷氏检验& I7 j4 b6 u+ N! r0 h3 ]
Rayleigh's Z, 雷氏Z值 " v: o, |5 t- {
Reciprocal, 倒数/ f. v+ s# N3 ~# S1 ~
Reciprocal transformation, 倒数变换
9 g+ y. K; c: e6 SRecording, 记录. n6 P. S+ @* o! I1 R8 p3 v' ]
Redescending estimators, 回降估计量
2 M8 P& _6 ~$ F* u" D3 }Reducing dimensions, 降维2 d, m# f& n! O, H1 r
Re-expression, 重新表达; a. [3 R6 E( }5 _: y" e
Reference set, 标准组: F5 D$ ]: s) U* }9 f
Region of acceptance, 接受域3 V7 ]& W2 [1 V7 ?' ~
Regression coefficient, 回归系数
+ e: {+ x. {% y$ NRegression sum of square, 回归平方和7 d2 D; v; R5 a5 D( k
Rejection point, 拒绝点
# y+ k& X" F0 Z8 uRelative dispersion, 相对离散度1 G, V* A+ \, v0 p
Relative number, 相对数
. x- `$ `3 n7 J6 dReliability, 可靠性; \2 y T7 T. I" l. r
Reparametrization, 重新设置参数* G4 U7 H; H4 O2 K$ E4 ~
Replication, 重复# ?+ B( B/ g7 }& I) X3 S
Report Summaries, 报告摘要# {, Z7 C0 c! P, \! c2 ?4 r
Residual sum of square, 剩余平方和- b8 C/ o" T$ [4 `9 T) [+ E
Resistance, 耐抗性6 i( b# T _3 j0 h, A: y/ A3 {( \
Resistant line, 耐抗线6 a$ v. y" P4 k e% Z* w+ S7 R8 Y
Resistant technique, 耐抗技术
' R, q/ ~! ?* W) X& x3 \R-estimator of location, 位置R估计量
+ E% j$ {5 z4 G8 XR-estimator of scale, 尺度R估计量9 q. H+ k( o) ^5 R) n" d: s
Retrospective study, 回顾性调查! F E0 m/ \2 w: x+ [ G
Ridge trace, 岭迹
7 t% [7 i# ?4 | s0 E, LRidit analysis, Ridit分析' E$ m; E# f7 z: q, T3 i2 o0 w
Rotation, 旋转+ v1 W- Q# Z% d( M( ]- H+ G+ d
Rounding, 舍入; B& y% L7 v8 {! ?
Row, 行/ O' \* `3 K2 V: M/ H' c
Row effects, 行效应
0 Q' ]* a& q3 q2 Y3 `2 o4 A9 `! J$ eRow factor, 行因素5 _$ j, m/ n! i* E% u1 n
RXC table, RXC表
i$ `) \% C0 p4 C3 K! C$ [9 FSample, 样本
4 a5 l9 {) Y: f# u: F# Z. [: sSample regression coefficient, 样本回归系数1 W1 |+ V5 S& Y6 M& z# ~
Sample size, 样本量) Y1 d$ I: I/ h* K
Sample standard deviation, 样本标准差
9 R" R% V& @ e$ ~8 a( mSampling error, 抽样误差
: z7 z9 n: A1 b, b4 R7 NSAS(Statistical analysis system ), SAS统计软件包
; |* G T% r, cScale, 尺度/量表
K& F8 D: w0 g) L3 A- P, ]2 UScatter diagram, 散点图" t1 q7 U/ L( u! L+ |1 o- A C
Schematic plot, 示意图/简图7 d) \9 U; R% O5 ~' q/ w; I: S
Score test, 计分检验" M- V( Q% Z- k) S6 n+ r
Screening, 筛检
1 R6 P) u% c- Q' T; u7 P0 OSEASON, 季节分析 2 C% k0 y' s+ g3 B( m
Second derivative, 二阶导数
( K$ y1 r+ R* [' T# s* z) h& Q! |Second principal component, 第二主成分7 D0 r& g l9 h- e. t
SEM (Structural equation modeling), 结构化方程模型 $ _- q( o% @4 H! ?4 U; Z4 V
Semi-logarithmic graph, 半对数图5 e+ n6 K0 b6 O( Q
Semi-logarithmic paper, 半对数格纸
& e" K& s) [! {4 y( W# p2 g: SSensitivity curve, 敏感度曲线6 G6 F8 T! C" ^, _3 [7 U8 Z
Sequential analysis, 贯序分析, X8 F8 D5 a$ E8 T
Sequential data set, 顺序数据集+ h |' |! ?6 Q9 L1 M
Sequential design, 贯序设计% G( @2 s. d. c$ S6 B/ \! N# P
Sequential method, 贯序法4 l) A7 a* z5 s% I$ X9 h
Sequential test, 贯序检验法/ W8 w" r: J6 S8 R( D
Serial tests, 系列试验2 v2 p9 H! H L p
Short-cut method, 简捷法
3 q6 k. W* x$ K/ h; N* x$ P* X+ YSigmoid curve, S形曲线: Q) ^4 J. x' J4 t7 M
Sign function, 正负号函数. Z6 M8 H4 N/ @' U9 S9 h( |
Sign test, 符号检验
7 w0 t7 `8 `+ l `Signed rank, 符号秩% D# ?$ r9 e" \0 R0 T, h" L+ ^+ u! n
Significance test, 显著性检验
% D6 s! O( j( ~. U2 r5 LSignificant figure, 有效数字' T: P' \' q& ]( \
Simple cluster sampling, 简单整群抽样0 v0 Y) {6 O& V3 o1 j% m
Simple correlation, 简单相关
* N! U+ |' U# n- R ^& \, nSimple random sampling, 简单随机抽样
+ G) C) e# P+ T( d# s4 c& dSimple regression, 简单回归
% x, J1 a) K! d, S% [$ [2 e$ asimple table, 简单表" X/ N% \! }4 g: i7 |( c% {% c
Sine estimator, 正弦估计量
6 K4 a9 { m# rSingle-valued estimate, 单值估计
) |8 f" ]5 t" Y+ U+ w! d4 nSingular matrix, 奇异矩阵' x+ ^" [( P) U
Skewed distribution, 偏斜分布
3 n8 @& Y& w8 m. d! BSkewness, 偏度
% L p; S: c2 E- `3 K& e7 [, HSlash distribution, 斜线分布' M9 A& Z x$ k
Slope, 斜率+ {2 M$ `2 @/ y* D
Smirnov test, 斯米尔诺夫检验
) |4 A+ |- X) g8 s% A7 ^$ XSource of variation, 变异来源
4 Y" \7 K) a/ F. i; }Spearman rank correlation, 斯皮尔曼等级相关
0 w3 _1 @5 L+ n& dSpecific factor, 特殊因子% K! J, u+ @ C g" R5 b4 d8 Q$ N7 A
Specific factor variance, 特殊因子方差
( S' L+ _8 Q3 M+ ZSpectra , 频谱
) ~3 D( y' U8 m, o/ _. ^Spherical distribution, 球型正态分布: U- g' v; [$ B! U
Spread, 展布) E, ]' D5 B8 T) t' \7 {7 @
SPSS(Statistical package for the social science), SPSS统计软件包( Q4 d: |( P5 ~5 X
Spurious correlation, 假性相关
, r4 ^. d2 e# Z$ S6 j4 O* {" iSquare root transformation, 平方根变换" v, a" Y* G9 Z3 S
Stabilizing variance, 稳定方差
0 J. P3 s. i/ }Standard deviation, 标准差5 a3 _( B" U$ g3 l! |
Standard error, 标准误
8 D* Q& q# p1 }Standard error of difference, 差别的标准误, {+ h4 W# Q) X& ~$ i" M5 @/ N
Standard error of estimate, 标准估计误差/ P" ^; M% y/ r& Y! `/ v7 N
Standard error of rate, 率的标准误 Z4 A- m$ d/ C$ f, ~
Standard normal distribution, 标准正态分布3 t+ }! Z% ^1 x0 c" j) V$ |0 o8 }" B
Standardization, 标准化
# l) ~% Q! b, `/ uStarting value, 起始值8 K, x7 Z2 D+ _1 v5 e9 m: M2 v
Statistic, 统计量7 Q" h- }, ]- d/ p( P) z
Statistical control, 统计控制
" _' Y* ]: q0 V# y& gStatistical graph, 统计图) {" ]7 B, o5 u
Statistical inference, 统计推断7 b& W2 _* W2 e ~
Statistical table, 统计表0 U! q; t0 b( o$ h* L) e# H
Steepest descent, 最速下降法
9 s6 e: Z3 G# U* fStem and leaf display, 茎叶图/ s9 \# U3 r4 L. Y
Step factor, 步长因子) [0 t y! M; c# a
Stepwise regression, 逐步回归" q( y& r. S) E) q
Storage, 存1 c) N/ w; N; p5 ?
Strata, 层（复数）
" d9 }! Y0 @# u6 e; O& x& @ RStratified sampling, 分层抽样
9 {' b7 C1 u' P- g5 j, L" S7 { XStratified sampling, 分层抽样
. ^5 l, X* U3 Z: zStrength, 强度; U3 t" Y; Y" q
Stringency, 严密性" s9 V* e6 @8 e
Structural relationship, 结构关系( d& P8 A9 G1 }' e: T
Studentized residual, 学生化残差/t化残差
$ Q+ p+ r3 ]6 i" N5 E: s0 aSub-class numbers, 次级组含量+ C* _ G7 Z( ?) f3 ^
Subdividing, 分割( Z( L% ^) L" K2 T6 |' z* s8 a: S
Sufficient statistic, 充分统计量
5 G8 h: s& t5 u1 N4 m# fSum of products, 积和
2 x. k: C. E g& K( t& @5 f2 TSum of squares, 离差平方和; D+ K" r9 `; B3 O! a Y' u
Sum of squares about regression, 回归平方和
6 S: z! j3 b1 l* ~( ?( [Sum of squares between groups, 组间平方和4 h( ]2 p" ^5 k& s. C4 F, z# n
Sum of squares of partial regression, 偏回归平方和
# O) p8 L& ^' E3 }4 {2 u( S7 iSure event, 必然事件- L4 k8 }7 t- V3 }- O; @+ H8 A
Survey, 调查
; X( v5 y% X7 C& r e8 `" G0 mSurvival, 生存分析3 d* a" T3 ^( X* D
Survival rate, 生存率1 L, ]( L$ M! o1 N# {, B% \
Suspended root gram, 悬吊根图. t- f& Q. K" n% E! |
Symmetry, 对称' _4 G6 f1 k8 K8 G) |
Systematic error, 系统误差 y1 C+ Q9 f5 m1 f; A4 u8 C+ @( y/ ?
Systematic sampling, 系统抽样
) d e. `) q r" L, ]5 b5 y8 kTags, 标签3 X! f4 y/ l3 P* D. U9 ^9 b
Tail area, 尾部面积
- {6 f5 S f) y+ K4 D9 mTail length, 尾长. H- h% v# J' o
Tail weight, 尾重
3 R U3 D# S6 G' E* CTangent line, 切线: x5 ~0 ~/ c. _3 Z5 g$ E. E
Target distribution, 目标分布
6 ~, _4 i# q# I! A- m5 A5 uTaylor series, 泰勒级数$ C; O( X5 m) o3 R% w/ C6 e0 R' s
Tendency of dispersion, 离散趋势7 R- G1 A& K) \1 \& s
Testing of hypotheses, 假设检验7 B; I* O% j j8 q
Theoretical frequency, 理论频数
% q' e- G" n5 Q7 J7 a, L) n8 p+ @Time series, 时间序列
6 R; `& D* S/ e# n6 g. KTolerance interval, 容忍区间8 B0 `; o2 Y: k% Y$ W7 ? Q a. F. F
Tolerance lower limit, 容忍下限
8 u! A) [8 F. B0 d2 s# mTolerance upper limit, 容忍上限# H& y+ K" o- c" c& z
Torsion, 扰率: T' `+ J. [' V) q( T% }( A
Total sum of square, 总平方和
; y O4 K$ G, _6 C: G+ dTotal variation, 总变异
' \$ p6 c7 F2 j, c' z& F. |1 BTransformation, 转换
1 W4 J0 D. Q% ^+ M* A# H( zTreatment, 处理
# K& n+ D7 x* z) e: sTrend, 趋势9 X( h& D7 ~4 ^4 N. y
Trend of percentage, 百分比趋势
! ~& B; t0 P, L. h4 O5 HTrial, 试验
: D3 W4 J5 g8 `: ^& lTrial and error method, 试错法8 [# ]4 q: p$ }1 \' A3 d# k
Tuning constant, 细调常数2 T' l* o( Q) w# W
Two sided test, 双向检验8 ? y0 z4 A o8 u1 s# P" c
Two-stage least squares, 二阶最小平方
- W% e0 y- L0 j1 T, ^; \7 S8 q& qTwo-stage sampling, 二阶段抽样
/ I0 C* u% t2 _8 w9 nTwo-tailed test, 双侧检验
# z, |1 q! A0 F. Z3 E* pTwo-way analysis of variance, 双因素方差分析
& G) A( T4 a! U9 Z* h' g8 RTwo-way table, 双向表0 I2 q! }% \5 D1 _' P, u
Type I error, 一类错误/α错误
8 W: m) \. ^3 j- @& V$ h% |; r: TType II error, 二类错误/β错误8 a1 O- B- F, D% s; p
UMVU, 方差一致最小无偏估计简称
7 J! f5 D" Z( F7 `8 Z iUnbiased estimate, 无偏估计
3 _- E4 X F& C+ y( uUnconstrained nonlinear regression , 无约束非线性回归4 W u9 P4 t) j5 l3 x; R o
Unequal subclass number, 不等次级组含量" f& ~& D4 S% O. S: j
Ungrouped data, 不分组资料/ U" v0 W$ a& K% c$ U+ L2 E* r( a
Uniform coordinate, 均匀坐标; B! q, I: Q* U; w# P
Uniform distribution, 均匀分布
+ G6 {6 m7 C+ E k, s5 IUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 r% h1 S1 q( A6 Y& _! _ o$ lUnit, 单元
0 q+ D ^# s4 }& w$ J( w6 pUnordered categories, 无序分类1 b% a8 p" e; S0 @
Upper limit, 上限
! i$ ?+ o" h( a6 sUpward rank, 升秩
: u5 G5 g% ]7 Z+ z) vVague concept, 模糊概念
% J/ e. K; r/ [& J. D0 u1 ~Validity, 有效性* G8 R" @, ^+ a6 ?% W1 M' X0 R
VARCOMP (Variance component estimation), 方差元素估计
! C' m! C- p. L/ rVariability, 变异性
$ i+ _$ W! R/ b2 C- [7 _7 Y- u7 r0 l1 yVariable, 变量( }1 q" W v& W) B5 S
Variance, 方差1 W' b: G5 L7 [# }1 ]8 b
Variation, 变异- E# N1 `# h! V" I: B4 `4 d5 [
Varimax orthogonal rotation, 方差最大正交旋转
2 H# A# F$ z) @8 E3 B, nVolume of distribution, 容积4 F: |. ~/ i# l% Z3 k1 Y6 h& P
W test, W检验0 \- Z: Q, g) d- v) k0 \ E0 j' M
Weibull distribution, 威布尔分布
4 O# g5 V( D7 |0 qWeight, 权数
5 p+ ?( u/ m& k0 J$ YWeighted Chi-square test, 加权卡方检验/Cochran检验5 `; m+ _' Z- `! Q. S& t
Weighted linear regression method, 加权直线回归
9 {! ]: a! ] ]: O) C+ K8 m eWeighted mean, 加权平均数
3 |1 a) r+ Y* f$ I) z3 v3 q2 sWeighted mean square, 加权平均方差
% u* _! u, o) p, Q& {2 O+ |6 w+ aWeighted sum of square, 加权平方和0 T( N" B6 M$ Y
Weighting coefficient, 权重系数0 t+ l; T O, E3 E0 s4 u# m
Weighting method, 加权法
: o9 u! G/ T' \. b* n3 ?7 A, H7 SW-estimation, W估计量% Y! M4 B9 ]6 l! @4 F1 s' h5 A
W-estimation of location, 位置W估计量
]7 p+ @2 Y% F ^/ uWidth, 宽度
5 }7 y5 x f/ ` u$ j, }" CWilcoxon paired test, 威斯康星配对法/配对符号秩和检验8 E& z% ?$ A/ X2 q; d
Wild point, 野点/狂点
0 |7 T% S; b2 G% r7 t1 _Wild value, 野值/狂值! t* L' X. [% E$ ?) N- z0 ~
Winsorized mean, 缩尾均值
7 f8 A& A3 Y1 i5 m5 EWithdraw, 失访
' N$ i! Y0 x& \6 |Youden's index, 尤登指数
& }; h. j/ x! l; BZ test, Z检验* e$ v; e8 M L) k% M
Zero correlation, 零相关+ q5 M" b0 w% `: [* |/ ^/ L6 E* y
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
